160 research outputs found
Embedded voices: building a non-learning culture within a learning enrichment programme
The researchers examined transcripts of comments made and dialogues engaged in by children, teachers and student teaching assistants during a 10-week enrichment programme for gifted and talented children aged 7–9 years. Attempts were made to match these utterances with the programme’s aims and aspirations as expressed in a promotional document. Little evidence of match was revealed, but considerable evidence did emerge of the extent to which dominant technical-rational discourses and practices permeate even privileged and non-state-sponsored educational environments, at the expense of children’s learning. Suggestions are made for foregrounding the processes of high quality pupil learning rather than the products of pupil performances in enrichment and extension programmes, and thereby for achieving greater congruence between this programme’s avowed aims and practice
pyveg: A Python package for analysing the time evolution of patterned vegetation using Google Earth Engine
Periodic vegetation patterns (PVP) arise from the interplay between forces that drive the
growth and mortality of plants. Inter-plant competition for resources, in particular water,
can lead to the formation of PVP. Arid and semi-arid ecosystems may be under threat due
to changing precipitation dynamics driven by macroscopic changes in climate. These regions
display some noteable examples of PVP, for example the “tiger bush” patterns found in West
Africa.
The morphology of the periodic pattern has been suggested to be linked to the resilience of
the ecosystem (Mander et al., 2017; Trichon et al., 2018). Using remote sensing techniques,
vegetation patterns in these regions can be studied, and an analysis of the resilience of the
ecosystem can be performed.
The pyveg package implements functionality to download and process data from Google Earth
Engine (GEE), and to subsequently perform a resilience analysis on the aquired data. PVP
images are quantified using network centrality metrics. The results of the analysis can be
used to search for typical early warning signals of an ecological collapse (Dakos et al., 2008).
Google Earth Engine Editor scripts are also provided to help researchers discover locations of
ecosystems which may be in decline.
pyveg is being developed as part of a research project looking for evidence of early warning
signals of ecosystem collapse using remote sensing data. pyveg allows such research to be
carried out at scale, and hence can be an important tool in understanding changing arid and
semi-arid ecosystem dynamics. An evolving list of PVP locations, obtained through both
literature and manual searches, is included in the package at pyveg/coordinates.py. The
structure of the package is outlined in Figure 1, and is discussed in more detail in the following
sections
Quantitatively monitoring the resilience of patterned vegetation in the Sahel
Patterning of vegetation in drylands is a consequence of localized feedback mechanisms. Such feedbacks also determine ecosystem resilience—i.e. the ability to recover from perturbation. Hence, the patterning of vegetation has been hypothesized to be an indicator of resilience, that is, spots are less resilient than labyrinths. Previous studies have made this qualitative link and used models to quantitatively explore it, but few have quantitatively analysed available data to test the hypothesis. Here we provide methods for quantitatively monitoring the resilience of patterned vegetation, applied to 40 sites in the Sahel (a mix of previously identified and new ones). We show that an existing quantification of vegetation patterns in terms of a feature vector metric can effectively distinguish gaps, labyrinths, spots, and a novel category of spot–labyrinths at their maximum extent, whereas NDVI does not. The feature vector pattern metric correlates with mean precipitation. We then explored two approaches to measuring resilience. First we treated the rainy season as a perturbation and examined the subsequent rate of decay of patterns and NDVI as possible measures of resilience. This showed faster decay rates—conventionally interpreted as greater resilience—associated with wetter, more vegetated sites. Second we detrended the seasonal cycle and examined temporal autocorrelation and variance of the residuals as possible measures of resilience. Autocorrelation and variance of our pattern metric increase with declining mean precipitation, consistent with loss of resilience. Thus, drier sites appear less resilient, but we find no significant correlation between the mean or maximum value of the pattern metric (and associated morphological pattern types) and either of our measures of resilience
Committed global warming risks triggering multiple climate tipping points
Many scenarios for limiting global warming to 1.5°C assume planetary-scale carbon dioxide removal sufficient to exceed anthropogenic emissions, resulting in radiative forcing falling and temperatures stabilizing. However, such removal technology may prove unfeasible for technical, environmental, political, or economic reasons, resulting in continuing greenhouse gas emissions from hard-to-mitigate sectors. This may lead to constant concentration scenarios, where net anthropogenic emissions remain non-zero but small, and are roughly balanced by natural carbon sinks. Such a situation would keep atmospheric radiative forcing roughly constant. Fixed radiative forcing creates an equilibrium “committed” warming, captured in the concept of “equilibrium climate sensitivity.” This scenario is rarely analyzed as a potential extension to transient climate scenarios. Here, we aim to understand the planetary response to such fixed concentration commitments, with an emphasis on assessing the resulting likelihood of exceeding temperature thresholds that trigger climate tipping points. We explore transients followed by respective equilibrium committed warming initiated under low to high emission scenarios. We find that the likelihood of crossing the 1.5°C threshold and the 2.0°C threshold is 83% and 55%, respectively, if today's radiative forcing is maintained until achieving equilibrium global warming. Under the scenario that best matches current national commitments (RCP4.5), we estimate that in the transient stage, two tipping points will be crossed. If radiative forcing is then held fixed after the year 2100, a further six tipping point thresholds are crossed. Achieving a trajectory similar to RCP2.6 requires reaching net-zero emissions rapidly, which would greatly reduce the likelihood of tipping events
Bayesian population receptive field modelling
We introduce a probabilistic (Bayesian) framework and associated software
toolbox for mapping population receptive fields (pRFs) based on fMRI data. This
generic approach is intended to work with stimuli of any dimension and is
demonstrated and validated in the context of 2D retinotopic mapping. The
framework enables the experimenter to specify generative (encoding) models of
fMRI timeseries, in which experimental manipulations enter a pRF model of
neural activity, which in turns drives a nonlinear model of neurovascular
coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal
and haemodynamic parameters are estimated together on a voxel-by-voxel or
region-of-interest basis using a Bayesian estimation algorithm (variational
Laplace). This offers several novel contributions to receptive field modelling.
The variance / covariance of parameters are estimated, enabling receptive
fields to be plotted while properly representing uncertainty about pRF size and
location. Variability in the haemodynamic response across the brain is
accounted for. Furthermore, the framework introduces formal hypothesis testing
to pRF analysis, enabling competing models to be evaluated based on their model
evidence (approximated by the variational free energy), which represents the
optimal tradeoff between accuracy and complexity. Using simulations and
empirical data, we found that parameters typically used to represent pRF size
and neuronal scaling are strongly correlated, which should be taken into
account when making inferences. We used the framework to compare the evidence
for six variants of pRF model using 7T functional MRI data and we found a
circular Difference of Gaussians (DoG) model to be the best explanation for our
data overall. We hope this framework will prove useful for mapping stimulus
spaces with any number of dimensions onto the anatomy of the brain.Comment: 30 pages, 10 figures. Code available at
https://github.com/pzeidman/BayespR
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Understanding the Effects of Long-duration Space Flight on Astronant Functional Task Performance
Space flight is known to cause alterations in multiple physiological systems including changes in sensorimotor, cardiovascular, and neuromuscular systems. These physiological changes cause balance, gait and visual disturbances, cardiovascular deconditioning, and loss of muscle mass and strength. These changes may affect a crewmember's ability to perform critical mission tasks immediately after landing on a planetary surface. To understand how changes in physiological function affect functional performance, an interdisciplinary pre- and postflight testing regimen, Functional Task Test (FTT), was developed to systematically evaluate both astronaut functional performance and related physiological changes. Ultimately this information will be used to assess performance risks and inform the design of countermeasures for exploration class missions. We are currently conducting the FTT study on International Space Station (ISS) crewmembers before and after 6-month expeditions. Additionally, in a corresponding study we are using the FTT protocol on subjects before and after 70 days of 6deg head-down bed-rest as an analog for space flight. Bed-rest provides the opportunity for us to investigate the role of prolonged axial body unloading in isolation from the other physiological effects produced by exposure to the microgravity environment of space flight. Therefore, the bed rest analog allows us to investigate the impact of body unloading on both functional tasks and on the underlying physiological factors that lead to decrement in performance and then compare them with the results obtained in our space flight study. Functional tests included ladder climbing, hatch opening, jump down, manual manipulation of objects and tool use, seat egress and obstacle avoidance, recovery from a fall and object translation tasks. Physiological measures included assessments of postural and gait control, dynamic visual acuity, fine motor control, plasma volume, heart rate, blood pressure, orthostatic intolerance, upper- and lower-body muscle strength, power, endurance, control, and neuromuscular drive. ISS crewmembers were tested three times before flight, and on 1, 6, and 30 days after landing. Bed-rest subjects were tested three times before bed-rest and immediately after getting up from bed-rest as well as 1, 6, and 12 days after reambulation
Pop stars and idolatry: an investigation of the worship of popular music icons, and the music and cult of Prince
New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism.
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood. Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits. In an expanded genome-wide association meta-analysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism
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